In supervised machine learning, variable ranking aims at sorting the input variables according to their relevance w.r.t. an output variable. In this paper, we propose a new relevan...
Multi-label learning is useful in visual object recognition when several objects are present in an image. Conventional approaches implement multi-label learning as a set of binary...
The problem of measuring "similarity" of objects arises in many applications, and many domain-specific measures have been developed, e.g., matching text across documents...
Many web documents are dynamic, with content changing in varying amounts at varying frequencies. However, current document search algorithms have a static view of the document con...
We consider the problem of reducing the dimensionality of labeled data for classification. Unfortunately, the optimal approach of finding the low-dimensional projection with minim...